Elon Musk - by Walter Isaacson

From the very beginning of his career, Musk was a demanding manager, contemptuous of the concept of work-life balance. At Zip2 and every subsequent company, he drove himself relentlessly all day and through much of the night, without vacations, and he expected others to do the same. His only indulgence was allowing breaks for intense video-game binges.

Musk restructured the company so that there was not a separate engineering department. Instead, engineers would team up with product managers. It was a philosophy that he would carry through to Tesla, SpaceX, and then Twitter. Separating the design of a product from its engineering was a recipe for dysfunction. Designers had to feel the immediate pain if something they devised was hard to engineer. He also had a corollary that worked well for rockets but less so for Twitter: engineers rather than the product managers should lead the team.

What struck his colleagues at PayPal, in addition to his relentless and rough personal style, was his willingness, even desire, to take risks. “Entrepreneurs are actually not risk takers,” says Roelof Botha. “They’re risk mitigators. They don’t thrive on risk, they never seek to amplify it, instead they try to figure out the controllable variables and minimize their risk.” But not Musk. “He was into amplifying risk and burning the boats so we could never retreat from it.” To Botha, Musk’s McLaren crash was like a metaphor: floor it and see how fast it goes. That made Musk fundamentally different from Thiel, who always focused on limiting risks. He and Hoffman once planned to write a book on their experience at PayPal. The chapter on Musk was going to be titled “The Man Who Didn’t Understand the Meaning of the Word ‘Risk.’ ” Risk addiction can be useful when it comes to driving people to do what seems impossible. “He’s amazingly successful getting people to march across a desert,” Hoffman says. “He has a level of certainty that causes him to put all of his chips on the table.” That was more than just a metaphor. Many years later, Levchin was at a friend’s bachelor pad hanging out with Musk. Some people were playing a high-stakes game of Texas Hold ’Em. Although Musk was not a card player, he pulled up to the table. “There were all these nerds and sharpsters who were good at memorizing cards and calculating odds,” Levchin says. “Elon just proceeded to go all in on every hand and lose. Then he would buy more chips and double down. Eventually, after losing many hands, he went all in and won. Then he said, ‘Right, fine, I’m done.’ ” It would be a theme in his life: avoid taking chips off the table; keep risking them. That would turn out to be a good strategy. “Look at the two companies he went on to build, SpaceX and Tesla,” says Thiel. “Silicon Valley wisdom would be that these were both incredibly crazy bets. But if two crazy companies work that everyone thought couldn’t possibly work, then you say to yourself, ‘I think Elon understands something about risk that everybody else doesn’t.’ ”

After listening to Musk describe his plan to send rockets to Mars, Hoffman was puzzled. “How is this a business?” he asked. Later Hoffman would realize that Musk didn’t think that way. “What I didn’t appreciate is that Elon starts with a mission and later finds a way to backfill in order to make it work financially,” he says. “That’s what makes him a force of nature.”

It’s useful to pause for a moment and note how wild it was for a thirty-year-old entrepreneur who had been ousted from two tech startups to decide to build rockets that could go to Mars. What drove him, other than an aversion to vacations and a childlike love of rockets, sci-fi, and A Hitchhiker’s Guide to the Galaxy? To his bemused friends at the time, and consistently in conversations over the ensuing years, he gave three reasons. He found it surprising—and frightening—that technological progress was not inevitable. It could stop. It could even backslide. America had gone to the moon. But then came the grounding of the Shuttle missions and an end to progress. “Do we want to tell our children that going to the moon is the best we did, and then we gave up?” he asks. Ancient Egyptians learned how to build the pyramids, but then that knowledge was lost. The same happened to Rome, which built aqueducts and other wonders that were lost in the Dark Ages. Was that happening to America? “People are mistaken when they think that technology just automatically improves,” he would say in a TED Talk a few years later. “It only improves if a lot of people work very hard to make it better.” Another motivation was that colonizing other planets would help ensure the survival of human civilization and consciousness in case something happened to our fragile planet. It may someday be destroyed by an asteroid or climate change or nuclear war. He had become fascinated by Fermi’s Paradox, named after the Italian American physicist Enrico Fermi, who in a discussion of alien life in the universe said, “But where is everyone?” Mathematically it seemed logical there were other civilizations, but the lack of any evidence raised the uncomfortable possibility that the Earth’s human species might be the only example of consciousness. “We’ve got this delicate candle of consciousness flickering here, and it may be the only instance of consciousness, so it’s essential we preserve it,” Musk says. “If we are able to go to other planets, the probable lifespan of human consciousness is going to be far greater than if we are stuck on one planet that could get hit by an asteroid or destroy its civilization.” His third motivation was more inspirational. It came from his heritage in a family of adventurers and his decision as a teenager to move to a country that had bred into its essence the spirit of pioneers. “The United States is literally a distillation of the human spirit of exploration,” he says. “This is a land of adventurers.” That spirit needed to be rekindled in America, he felt, and the best way to do that would be to embark on a mission to colonize Mars. “To have a base on Mars would be incredibly difficult, and people will probably die along the way, just as happened in the settling of the United States. But it will be incredibly inspiring, and we must have inspiring things in the world.” Life cannot be merely about solving problems, he felt. It also had to be about pursuing great dreams. “That’s what can get us up in the morning.” Faring to other planets would be, Musk believed, one of the significant advances in the story of humanity. “There are only a handful of really big milestones: single-celled life, multicellular life, differentiation of plants and animals, life extending from the oceans to land, mammals, consciousness,” he says. “On that scale, the next important step is obvious: making life multiplanetary.” There was something exhilarating, and also a bit unnerving, about Musk’s ability to see his endeavors as having epoch-making significance. As Max Levchin drily puts it, “One of Elon’s greatest skills is the ability to pass off his vision as a mandate from heaven.”

He employed some first-principles thinking, drilling down to the basic physics of the situation and building up from there. This led him to develop what he called an “idiot index,” which calculated how much more costly a finished product was than the cost of its basic materials. If a product had a high idiot index, its cost could be reduced significantly by devising more efficient manufacturing techniques. Rockets had an extremely high idiot index. Musk began calculating the cost of carbon fiber, metal, fuel, and other materials that went into them. The finished product, using the current manufacturing methods, cost at least fifty times more than that.

Musk’s space adventure had begun as a nonprofit endeavor to inspire interest in a mission to Mars, but now he had the combination of motivations that would mark his career. He would do something audacious that was driven by a grand idea. But he also wanted it to be practical and profitable, so that it could sustain itself. That meant using the rockets to launch commercial and government satellites.

Musk incorporated Space Exploration Technologies in May 2002. At first he called the company by its initials, SET. A few months later, he highlighted his favorite letter by moving to a more memorable moniker, SpaceX. Its goal, he said in an early presentation, was to launch its first rocket by September 2003 and to send an unmanned mission to Mars by 2010. Thus continued the tradition he had established at PayPal: setting unrealistic timelines that transformed his wild notions from being completely insane to being merely very late.

One thing that Mueller insisted on was that Musk put two years’ worth of compensation into escrow. He was not an internet millionaire, and he did not want to take the chance of being unpaid if the venture failed. Musk agreed. It did, however, cause him to consider Mueller an employee rather than a cofounder of SpaceX. It was a fight he had regarding PayPal and would have again involving Tesla. If you’re unwilling to invest in a company, he felt, you shouldn’t qualify as a founder. “You cannot ask for two years of salary in escrow and consider yourself a cofounder,” he says. “There’s got to be some combination of inspiration, perspiration, and risk to be a cofounder.”

In laying out the factory, Musk followed his philosophy that the design, engineering, and manufacturing teams would all be clustered together. “The people on the assembly line should be able to immediately collar a designer or engineer and say, ‘Why the fuck did you make it this way?’ ” he explained to Mueller. “If your hand is on a stove and it gets hot, you pull it right off, but if it’s someone else’s hand on the stove, it will take you longer to do something.”

As his team grew, Musk infused it with his tolerance for risk and reality-bending willfulness. “If you were negative or thought something couldn’t be done, you were not invited to the next meeting,” Mueller recalls. “He just wanted people who would make things happen.” It was a good way to drive people to do what they thought was impossible. But it was also a good way to become surrounded by people afraid to give you bad news or question a decision.

Musk’s Rules for Rocket-Building

  • Question every cost.

  • Have a maniacal sense of urgency. Musk insisted on setting unrealistic deadlines even when they weren’t necessary, such as when he ordered test stands to be erected in weeks for rocket engines that had not yet been built. “A maniacal sense of urgency is our operating principle,” he repeatedly declared. The sense of urgency was good for its own sake. It made his engineers engage in first-principles thinking. But as Mueller points out, it was also corrosive. “If you set an aggressive schedule that people think they might be able to make, they will try to put out extra effort,” he says. “But if you give them a schedule that’s physically impossible, engineers aren’t stupid. You’ve demoralized them. It’s Elon’s biggest weakness.” Steve Jobs did something similar. His colleagues called it his reality-distortion field. He set unrealistic deadlines, and when people balked, he would stare at them without blinking and say, “Don’t be afraid, you can do it.” Although the practice demoralized people, they ended up accomplishing things that other companies couldn’t.

  • Learn by failing. Musk took an iterative approach to design. Rockets and engines would be quickly prototyped, tested, blown up, revised, and tried again, until finally something worked. Move fast, blow things up, repeat. “It’s not how well you avoid problems,” Mueller says. “It’s how fast you figure out what the problem is and fix it.”

  • Improvise.

Musk met with officials at NASA headquarters in May 2004 and, ignoring the advice of Shotwell, decided to sue them over the Kistler contract. “Everyone told me that it might mean we would never be able to work with NASA,” Musk says. “But what they did was wrong and corrupt, so I sued.” SpaceX ended up winning the dispute, and NASA was ordered to open the project to competitive bidding. SpaceX was able to win a significant portion of it.

The victory was crucial not only for SpaceX but for the American space program. It promoted an alternative to the “cost-plus” contracts that NASA and the Defense Department had generally been using. Under those contracts, the government kept control of a project—such as building a new rocket or engine or satellite—and issued detailed specifications of what it wanted done. It would then award contracts to big companies such as Boeing or Lockheed Martin, which would be paid all of their costs plus a guaranteed profit. This approach became standard during World War II to give the government complete control over the development of weapons and to prevent the perception that contractors were war-profiteering. On his trip to Washington, Musk testified before a Senate committee and pushed a different approach. The problem with a cost-plus system, he argued, was that it stymied innovation. If the project went over budget, the contractor would get paid more. There was little incentive for the cozy club of cost-plus contractors to take risks, be creative, work fast, or cut costs. “Boeing and Lockheed just want their cost-plus gravy trains,” he says. “You just can’t get to Mars with that system. They have an incentive never to finish. If you never finish a cost-plus contract, then you suckle on the tit of the government forever.” SpaceX pioneered an alternative in which private companies bid on performing a specific task or mission, such as launching government payloads into orbit. The company risked its own capital, and it would be paid only if and when it delivered on certain milestones. This outcomes-based, fixed-price contracting allowed the private company to control, within broad parameters, how its rockets were designed and built. There was a lot of money to be made if it built a cost-efficient rocket that succeeded, and a lot of money to be lost if it failed. “It rewards results rather than waste,” Musk says.

One of the most important decisions that Elon Musk made about Tesla—the defining imprint that led to its success and its impact on the auto industry—was that it should make its own key components, rather than piecing together a car with hundreds of components from independent suppliers. Tesla would control its own destiny—and quality and costs and supply chain—by being vertically integrated. Creating a good car was important. Even more important was creating the manufacturing processes and factories that could mass-produce them, from the battery cells to the body.

Musk has a rule about responsibility: every part, every process, and every specification needs to have a name attached. He can be quick to personalize blame when something goes wrong.

“It’s not the product that leads to success. It’s the ability to make the product efficiently. It’s about building the machine that builds the machine. In other words, how do you design the factory?” It was a guiding principle that Musk would make his own.

Over the years, one criticism of Tesla has been that the company was “bailed out” or “subsidized” by the government in 2009. In fact, Tesla did not get money from the Treasury Department’s Troubled Asset Relief Program (TARP), commonly known as “the bailout.” Under that program, the government lent $18.4 billion to General Motors and Chrysler as they went through bankruptcy restructuring. Tesla did not apply for any TARP or stimulus package money. What Tesla did get in June 2009 was $465 million in interest-bearing loans from a Department of Energy program.

Over the years, one criticism of Tesla has been that the company was “bailed out” or “subsidized” by the government in 2009. In fact, Tesla did not get money from the Treasury Department’s Troubled Asset Relief Program (TARP), commonly known as “the bailout.” Under that program, the government lent $18.4 billion to General Motors and Chrysler as they went through bankruptcy restructuring. Tesla did not apply for any TARP or stimulus package money. What Tesla did get in June 2009 was $465 million in interest-bearing loans from a Department of Energy program. The Advanced Technology Vehicles Manufacturing Loan Program lent money to companies to make electric or fuel-efficient cars. Ford, Nissan, and Fisker Automotive also got loans. The Energy Department’s loan to Tesla was not an immediate infusion of cash. Unlike the bailout money to GM and Chrysler, the loan money was tied to actual expenses. “We had to spend money and then submit invoices to the government,” Musk explains. So the first check did not come until early 2010. Three years later, Tesla repaid its loan along with $12 million interest. Nissan repaid in 2017, Fisker went bankrupt, and as of 2023 Ford still owed the money.

To be the chief engineer for the Model S, Musk hired Peter Rawlinson, a genteel Englishman who had worked on car bodies for Lotus and Land Rover. Together they came up with a way to do more than merely place the battery pack under the floor of the car. They engineered it so that the pack became an element of the car’s structure. It was an example of Musk’s policy that the designers sketching the shape of the car should work hand in glove with the engineers who were determining how the car would be built. “At other places I worked,” von Holzhausen says, “there was this throw-it-over-the-fence mentality, where a designer would have an idea and then send it to an engineer, who sat in a different building or in a different country.” Musk put the engineers and designers in the same room. “The vision was that we would create designers who thought like engineers and engineers who thought like designers,” von Holzhausen says. This followed the principle that Steve Jobs and Jony Ive had instilled at Apple: design is not just about aesthetics; true industrial design must connect the looks of a product to its engineering. “In most people’s vocabularies, design means veneer,” Jobs once explained. “Nothing could be further from the meaning of design. Design is the fundamental soul of a man-made creation that ends up expressing itself in successive outer layers.”

Beginning with the theology of globalization in the 1980s, and relentlessly driven by cost-cutting CEOs and their activist investors, American companies shut down domestic factories and offshored manufacturing. The trend accelerated in the early 2000s, when Tesla was getting started. Between 2000 and 2010, the U.S. lost one-third of its manufacturing jobs. By sending their factories abroad, American companies saved labor costs, but they lost the daily feel for ways to improve their products. Musk bucked this trend, largely because he wanted to have tight control of the manufacturing process. He believed that designing the factory to build a car—“the machine that builds the machine”—was as important as designing the car itself. Tesla’s design-manufacturing feedback loop gave it a competitive advantage, allowing it to innovate on a daily basis.

Both Musk and Bezos had a vision for what would make space travel feasible: rockets that were reusable. Bezos’s focus was on creating the sensors and software to guide a rocket to a soft landing on Earth. But that was only part of the challenge. The greater difficulty was to put all of those features on a rocket that was still light enough, and whose engines had enough thrust, to make it into orbit. Musk focused obsessively on this physics problem. He liked to muse, half-jokingly, that we Earthlings live in a gamelike simulation created by clever overlords with a sense of humor. They made gravity on Mars and the moon weak enough that launching into orbit would be easy. But on Earth, the gravity seems perversely calibrated to make reaching orbit just barely possible.

One way to assure AI alignment, Musk felt, was to tie the bots closely to humans. They should be an extension of the will of individuals, rather than systems that could go rogue and develop their own goals and intentions. That would become one of the rationales for Neuralink, the company he would found to create chips that could connect human brains directly to computers. He also realized that success in the field of artificial intelligence would come from having access to huge amounts of real-world data that the bots could learn from. One such gold mine, he realized at the time, was Tesla, which collected millions of frames of video each day of drivers handling different situations. “Probably Tesla will have more real-world data than any other company in the world,” he said. Another trove of data, he would later come to realize, was Twitter, which by 2023 was processing 500 million posts per day from humans.

Google’s autopilot program, eventually named Waymo, used a laser-radar device known as LiDAR, an acronym for “light detection and ranging.” Musk resisted the use of LiDAR and other radar-like instruments, insisting that a self-driving system should use only visual data from cameras. It was a case of first principles: humans drove using only visual data; therefore machines should be able to. It was also an issue of cost. As always, Musk focused not just on the design of a product but also on how it would be manufactured in large numbers. “The problem with Google’s approach is that the sensor system is too expensive,” he said in 2013. “It’s better to have an optical system, basically cameras with software that is able to figure out what’s going on just by looking at things.”

Ever since the development of assembly lines in the early 1900s, most factories have been designed in two steps. First, the line is set up with workers doing specific tasks at each station. Then, when the kinks are worked out, robots and other machines are gradually introduced to take over some of the work. Musk did the reverse. In his vision for a modern “alien dreadnought” factory, he began by automating every task possible. “We had this enormously automated production line that used tons of robots,” says Straubel. “There was one problem. It didn’t work.” One night, Musk was walking through the Nevada battery pack factory with his posse—Omead Afshar, Antonio Gracias, and Tim Watkins—and they noticed a delay at a workstation where a robotic arm was sticking cells to a tube. The machine had a problem gripping the material and getting aligned. Watkins and Gracias went over to a table and tried to do the process by hand. They could do it more reliably. They called Musk over and calculated how many humans it would take to get rid of the machine. Workers were hired to replace the robot, and the assembly line moved more quickly. Musk flipped from being an apostle of automation to a new mission he pursued with similar zeal: find any part of the line where there was a holdup and see if de-automation would make it go faster. “We began sawing robots out of the production line and throwing them into the parking lot,” Straubel says. On one weekend, they marched through the factory painting marks on machinery to be jettisoned. “We put a hole in the side of the building just to remove all that equipment,” Musk says. The experience became a lesson that would become part of Musk’s production algorithm. Always wait until the end of designing a process—after you have questioned all the requirements and deleted unnecessary parts—before you introduce automation.

In the middle of the Fremont factory is the main conference room, known as Jupiter. Musk used it as his office, meeting space, haven from mental torments, and sometimes a place to sleep. An array of screens, blinking and updating like stock displays, tracked in real time the total output of the factory and of each workstation. Musk had come to realize that designing a good factory was like designing a microchip. It was important to create, in each patch, the right density, flow, and processes. So he paid the most attention to a monitor that showed each station on the assembly line with a green or red light indicating whether it was flowing properly. There were also green and red lights at the stations themselves, so Musk was able to walk the floor and home in on trouble spots. His team called it “walk to the red.”

The algorithm At any given production meeting, whether at Tesla or SpaceX, there is a nontrivial chance that Musk will intone, like a mantra, what he calls “the algorithm.” It was shaped by the lessons he learned during the production hell surges at the Nevada and Fremont factories. His executives sometimes move their lips and mouth the words, like they would chant the liturgy along with their priest. “I became a broken record on the algorithm,” Musk says. “But I think it’s helpful to say it to an annoying degree.” It had five commandments: 1. Question every requirement. Each should come with the name of the person who made it. You should never accept that a requirement came from a department, such as from “the legal department” or “the safety department.” You need to know the name of the real person who made that requirement. Then you should question it, no matter how smart that person is. Requirements from smart people are the most dangerous, because people are less likely to question them. Always do so, even if the requirement came from me. Then make the requirements less dumb. 2. Delete any part or process you can. You may have to add them back later. In fact, if you do not end up adding back at least 10% of them, then you didn’t delete enough. 3. Simplify and optimize. This should come after step two. A common mistake is to simplify and optimize a part or a process that should not exist. 4. Accelerate cycle time. Every process can be speeded up. But only do this after you have followed the first three steps. In the Tesla factory, I mistakenly spent a lot of time accelerating processes that I later realized should have been deleted. 5. Automate. That comes last. The big mistake in Nevada and at Fremont was that I began by trying to automate every step. We should have waited until all the requirements had been questioned, parts and processes deleted, and the bugs were shaken out. The algorithm was sometimes accompanied by a few corollaries, among them: All technical managers must have hands-on experience. For example, managers of software teams must spend at least 20% of their time coding. Solar roof managers must spend time on the roofs doing installations. Otherwise, they are like a cavalry leader who can’t ride a horse or a general who can’t use a sword. Comradery is dangerous. It makes it hard for people to challenge each other’s work. There is a tendency to not want to throw a colleague under the bus. That needs to be avoided. It’s OK to be wrong. Just don’t be confident and wrong. Never ask your troops to do something you’re not willing to do. Whenever there are problems to solve, don’t just meet with your managers. Do a skip level, where you meet with the level right below your managers. When hiring, look for people with the right attitude. Skills can be taught. Attitude changes require a brain transplant. A maniacal sense of urgency is our operating principle. The only rules are the ones dictated by the laws of physics. Everything else is a recommendation.

Musk’s friends began referring to his crises as his going “open-loop.” The term is used for an object, such as a bullet as opposed to a guided missile, that has no feedback mechanism to provide it with guidance. “Whenever our friends become open-loop, meaning that they don’t have iterative feedback and don’t seem to care about the outcomes, we take it upon ourselves to let each other know,” Kimbal says.

Every year, he had regularly predicted in public that a fully autonomous car was just a year or so away. Except that it wasn’t. Full autonomy continued to be a receding mirage, always a year or so away. Nevertheless, Musk concluded that the best way to raise more funding was to hold a dramatic demonstration showing that autonomous vehicles were the way that the company would become phenomenally profitable. He was convinced that his team could put on a demo—even show off a credible prototype—of what the future would be. He set a marker for four weeks away: on April 22, 2019, they would demonstrate a version of a partially self-driving car for what would be Tesla’s first Autonomy Day. “We have to show people this is real,” he said, even though it wasn’t yet. The result was another of Musk’s hallmark surges: an all-hands-on-deck 24/7 frenzy to produce an outcome by a deadline that was artificial and unrealistic.

Beginning with the retirement of the Space Shuttle in 2011, the United States experienced a lapse in ability, will, and imagination that was astonishing for a nation that, two generations earlier, had made nine missions to the moon. For almost a decade after the last Shuttle mission, the nation had not been able to send humans into space. It was forced to rely on Russian rockets to get its astronauts to the International Space Station. In 2020, SpaceX changed that. That May, a Falcon 9 rocket topped with a Crew Dragon capsule was ready to carry two NASA astronauts to the International Space Station—the first-ever launch of humans into orbit by a private company.

Bezos and Musk were alike in some respects. They both disrupted industries through passion, innovation, and force of will. They were both abrupt with employees, quick to call things stupid, and enraged by doubters and naysayers. And they both focused on envisioning the future rather than pursuing short-term profits. When asked if he even knew how to spell “profit,” Bezos answered, “P-r-o-p-h-e-t.” But when it came to drilling down on the engineering, they were different. Bezos was methodical. His motto was gradatim ferociter, or “Step by step, ferociously.” Musk’s instinct was to push and surge and drive people toward insane deadlines, even if it meant taking risks. Bezos was skeptical, indeed dismissive of Musk’s practice of spending hours at engineering meetings making technical suggestions and issuing abrupt orders. Former employees at SpaceX and Tesla told him, he says, that Musk rarely knew as much as he claimed and that his interventions were usually unhelpful or outright problematic. For his part, Musk felt that Bezos was a dilettante whose lack of focus on the engineering was one reason Blue Origin had made less progress than SpaceX. In an interview in late 2021, he grudgingly praised Bezos for having “reasonably good engineering aptitude,” but then added, “But he does not seem to be willing to spend mental energy getting into the details of engineering. The devil’s in the details.”

Hughes appreciated Musk’s all-in mindset. “He’s willing to just throw his entire being at his mission, and that’s what he expects in return,” he says. “That has a good and bad side. You definitely realize that you’re a tool being used to achieve this larger objective, and that’s great. But sometimes, tools get worn down and he feels he can just replace that tool.” Indeed, as he showed when he bought Twitter, Musk does feel that way. He thinks that when people want to prioritize their comfort and leisure they should leave.

There are two types of lieutenants Musk favors: the Red Bulls, such as Mark Juncosa, who are highly caffeinated and voluble as they purge-pulse ideas, and the Spocks, whose measured monotones give them an aura of Vulcan competence.

Some of the most important technology leaps in the digital age involved advances in the way that humans and machines communicate with each other, known as “human-computer interfaces.” The psychologist and engineer J. C. R. Licklider, who worked on air-defense systems that tracked planes on a monitor, wrote a seminal paper in 1960 titled “Man-Computer Symbiosis,” showing how video displays could “get a computer and a person thinking together.” He added, “The hope is that, in not too many years, human brains and computing machines will be coupled together very tightly.”

The ultimate human-machine interface, Musk realized, would be a device that connected our computers directly to our brains, such as a chip inside our skull that could send our brain signals to a computer and receive signals back. That could allow information to flow back and forth up to a million times faster. “Then you could have true human-machine symbiosis,” he says. In other words, it would assure that humans and machines would work together as partners. To make this happen, he founded, in late 2016, a company that he dubbed Neuralink, which would implant small chips into the brain and allow humans to mind-meld with computers. Like Optimus, the idea for Neuralink was inspired by science fiction, most notably the Culture space-travel novels by Iain Banks, which feature a human-machine interface technology called “neural lace” that is implanted into people and can connect all of their thoughts to a computer. “When I first read Banks,” he says, “it struck me that this idea had a chance of protecting us on the artificial intelligence front.”

One key to understanding Musk—his intensity, focus, competitiveness, die-hard attitudes, and love of strategy—is through his passion for video games. Hours of immersion became the way he let off (or built up) steam and honed his tactical skills and strategic thinking for business.

Polytopia Life Lessons

  • Empathy is not an asset. “He knows that I have an empathy gene, unlike him, and it has hurt me in business,” Kimbal says. “Polytopia taught me how he thinks when you remove empathy. When you’re playing a video game, there is no empathy, right?”

  • Play life like a game. “I have this feeling,” Zilis once told Musk, “that as a kid you were playing one of these strategy games and your mom unplugged it, and you just didn’t notice, and you kept playing life as if it were that game.”

  • Do not fear losing. “You will lose,” Musk says. “It will hurt the first fifty times. When you get used to losing, you will play each game with less emotion.” You will be more fearless, take more risks.

  • Be proactive. “I’m a little bit Canadian pacifist and reactive,” Zilis says. “My gameplay was a hundred percent reactive to what everyone else was doing, as opposed to thinking through my best strategy.” She realized that, like many women, this mirrored the way she behaved at work. Both Musk and Mark Juncosa told her that she could never win unless she took charge of setting the strategy.

  • Optimize every turn. In Polytopia, you get only thirty turns, so you need to optimize each one. “Like in Polytopia, you only get a set number of turns in life,” Musk says. “If we let a few of them slide, we will never get to Mars.”

  • Double down. “Elon plays the game by always pushing the edge of what’s possible,” Zilis says. “And he’s always doubling down and putting everything back in the game to grow and grow. And it’s just like he’s just done his whole life.”

  • Pick your battles. In Polytopia, you might find yourself surrounded by six or more tribes, all taking swipes at you. If you swipe back at all of them, you’re going to lose. Musk never fully mastered that lesson, and Zilis found herself coaching him on it. “Dude, like, everyone’s swiping at you right now, but if you swipe back at too many, you’ll run out of resources,” she told him. She called that approach “front minimization.” It was a lesson she also tried and failed to teach him about his behavior on Twitter.

  • Unplug at times. “I had to stop playing because it was destroying my marriage,” Kimbal says. Shivon Zilis also deleted Polytopia from her phone. So did Grimes. And, for a while, Musk did so as well. “I had to take Polytopia off my phone because it was taking up too many brain cycles,” he says. “I started dreaming about Polytopia.” But the lesson about unplugging was another one that Musk never mastered. After a few months, he put the game back onto his phone and was playing again.

When Musk announced his plans to build Optimus in August 2021, an actress dressed in a white body suit tottered around the stage emulating a robot. A few days later, Tesla’s design chief, Franz von Holzhausen, convened a group to begin building the real thing: a robot that could emulate a human. Musk gave one directive: it was to be a humanoid robot. In other words, it was supposed to look like a person rather than a mechanical contraption with wheels or four legs like Boston Dynamics and others were making. Most workspaces and tools are designed to accommodate the way humans do things, so Musk believed that a robot should approximate human forms in order to operate naturally. “We want to make it as human as possible,” von Holzhausen told the ten engineers and designers seated around his conference table. “But we can also add improvements to what humans can do.”

Self-driving cars, Musk believed, would do more than merely free folks from the drudgery of driving. They would, to a large extent, eliminate the need for people to own cars. The future would belong to the Robotaxi: a driverless vehicle that would appear when you summoned it, take you to your destination, then ride off to the next passenger. Some might be owned by individuals, but most would be owned by fleet companies or Tesla itself.

Between Twitterland and the Muskverse was a radical divergence in outlook that reflected two different mindsets about the American workplace. Twitter prided itself on being a friendly place where coddling was considered a virtue. “We were definitely very high-empathy, very caring about inclusion and diversity; everyone needs to feel safe here,” says Leslie Berland, who was chief marketing and people officer until she was fired by Musk. The company had instituted a permanent work-from-home option and allowed a mental “day of rest” each month. One of the commonly used buzzwords at the company was “psychological safety.” Care was taken not to discomfort. Musk let loose a bitter laugh when he heard the phrase “psychological safety.” It made him recoil. He considered it to be the enemy of urgency, progress, orbital velocity. His preferred buzzword was “hardcore.” Discomfort, he believed, was a good thing. It was a weapon against the scourge of complacency. Vacations, flower-smelling, work-life balance, and days of “mental rest” were not his thing.

When the dust settled, about 75 percent of the Twitter workforce had been cut. There were just under eight thousand employees when Musk took over on October 27. By mid-December, there were just over two thousand. Musk had wrought one of the greatest shifts in corporate culture ever. Twitter had gone from being among the most nurturing workplaces, replete with free artisanal meals and yoga studios and paid rest days and concern for “psychological safety,” to the other extreme. He did it not only for cost reasons. He preferred a scrappy, hard-driven environment where rabid warriors felt psychological danger rather than comfort.

For years, Tesla’s Autopilot system relied on a rules-based approach. It took visual data from a car’s cameras and identified such things as lane markings, pedestrians, vehicles, traffic signals, and anything else in range of the eight cameras. Then the software applied a set of rules, such as Stop when the light is red; Go when it’s green; Stay in the middle of the lane markers; Don’t cross double-yellow lines into incoming traffic; Proceed through an intersection only when there are no cars coming fast enough to hit you; and so on. Tesla’s engineers manually wrote and updated hundreds of thousands of lines of C++ code to apply these rules to complex situations. The neural network planner project that Shroff was working on would add a new layer. “Instead of determining the proper path of the car based only on rules,” Shroff says, “we determine the car’s proper path by also relying on a neural network that learns from millions of examples of what humans have done.” In other words, it’s human imitation. Faced with a situation, the neural network chooses a path based on what humans have done in thousands of similar situations. It’s like the way humans learn to speak and drive and play chess and eat spaghetti and do almost everything else; we might be given a set of rules to follow, but mainly we pick up the skills by observing how other people do them. It was the approach to machine learning envisioned by Alan Turing in his 1950 paper, “Computing Machinery and Intelligence.”

The fuel for AI is data. The new chatbots were being trained on massive amounts of information, such as billions of pages on the internet and other documents. Google and Microsoft, with their search engines and cloud services and access to emails, had huge gushers of data to help train these systems. What could Musk bring to the party? One asset was the Twitter feed, which included more than a trillion tweets posted over the years, five hundred million added each day. It was humanity’s hive mind, the world’s most timely data set of real-life human conversations, news, interests, trends, arguments, and lingo. Plus it was a great training ground for a chatbot to test how real humans react to its responses. The value of this data feed was not something Musk considered when buying Twitter. “It was a side benefit, actually, that I realized only after the purchase,” he says. Twitter had rather loosely permitted other companies to make use of this data stream. In January, Musk convened a series of late-night meetings in his Twitter conference room to work out ways to charge for it. “It’s a monetization opportunity,” he told the engineers. It was also a way to restrict Google and Microsoft from using this data to improve their AI chatbots. There was another data trove that Musk had: the 160 billion frames per day of video that Tesla received and processed from the cameras on its cars. This data was different from the text-based documents that informed chatbots. It was video data of humans navigating in real-world situations. It could help create AI for physical robots, not just text-generating chatbots. The holy grail of artificial general intelligence was building machines that could operate like humans in physical spaces, such as factories and offices and on the surface of Mars, not just wow us with disembodied chatting. Tesla and Twitter together could provide the data sets and the processing capability for both approaches: teaching machines to navigate in physical space and to answer questions in natural language.